Prevention over detection
For detect-and-respond vendors, the alert is the business model — they profit from the chase and the cleanup. We didn't extend the old model. We replaced it: neutralize threats before they breach.
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Why Salience
Three convictions that drive everything we build
We didn't add AI — we're made of it. But not the AI you're thinking of: no GenAI, no LLM, no SLM, no MCP gateway, and no dependency on them whatsoever. No model bolted onto a legacy scanner, no agentic framework wrapped around someone else's language model. Our architecture is neuromorphic — engineered to defend the AI era, native, not retrofitted.
Comprehension over signatures
Neuromorphic mathematics reads the intent inside an AI interaction — catching novel techniques that carry no prior signature. Detection tools record what happened; we anticipate what's about to.
No kernel agent by design
A userspace host sensor — not a kernel agent — running in the user's session with native OS APIs, no kernel extension, driver, EDR hook, or root, paired with an AI-aware extension in the browser. Coverage at the point of interaction, across both data planes — with no dependency on GenAI, LLMs, SLMs, or MCP gateways, and zero token cost. Flat-cost by design.
The difference
Everyone says “AI security.”
Almost nobody means this.
Wrap an LLM in guardrails and you inherit the adversary’s model. Ship telemetry to a server and you inherit the delay. We did neither.
| SalienceCyber.ai | LLM guardrail / "GPT wrapper" | Post-collection analytics | EDR / SIEM | |
|---|---|---|---|---|
| Where it sits | In-line, at the point of interaction | In the request path, as a proxy | On a server, after the fact | On the host, after execution |
| What it reads | Intent | Tokens | Logs | Artifacts and behaviour |
| Zero-signature attacks | Anticipated | Bounded by the model's training | After the fact, on a copy | Rarely |
| Decision latency | Microseconds · no model round-trip | A model round-trip | Minutes to hours | After execution |
| What it costs | Flat. Zero token cost | Metered per token | Per GB stored and queried | Per endpoint, plus storage |
| Surface it adds | None | Prompt injection. Model drift. | A second copy of your data | A kernel shim or an agent |
| What you are left with | The interaction never executes | An alert. Maybe a block. | A report | A ticket |
Same words. Different architecture. Different outcome.
What design partners are saying
Your employees are using AI tools you can’t see. SalienceCyber.ai fixes that. It captures every AI interaction on the endpoint and turns it into one clean audit trail — visibility and enforcement in the same product, without an LLM sitting in the critical path or another EDR integration to maintain.